• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.131-140
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• 1999

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the objectives of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the ramp junctions of freeway with 70mph speed limit. From the traffic analyses, and model constructions and verifications for delay prediction on the ramp junctions of freeway, the following results were obtained: ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junction of freeway. ⅲ) The speed-occupancy curve showed a remarkable shift based on the occupancies observed ; Od < 9% and Od$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under Od$\geq$9%, but lowly for delay predicion on the ramp junctions of freeway under Od<9%. Rather, the driver characteristics or transportation conditions around the freeway were through to be a little higher explanatory for the delay perdiction under Od<9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.205-216
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• 2008

Urban freeway is defined as the roadway with 4 lanes or more which requires a high design criteria for handling a large capacity of vehicles rapidly as a high-speed exclusive roadway in the city. However, most of the urban freeways suffer from severe traffic congestion due to the increased traffic exceeding their capacities regardless of the morning and afternoon rushhours or the inbound and outbound directions. The purpose in this study is to collect and investigate the real-time traffic characteristics based on the ramp junction influence areas of the urban freeway connected with the Busan port, compare and analyze the traffic characteristic relationship for each lane within the ramp junction influence areas, and finally assess and suggest the optimal capacity for each lane within the ramp junction influence areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.215-222
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• 2010

Average speed denotes a travel speed based on the average travel time of vehicles to traverse a segment of roadway, and average travel speed is used as a measure of effectiveness (MOE) suggested in the highway capacity manual (HCM) for evaluating the level of service (LOS) of roadway. Most of the urban freeways in our country are having congestion problem regardless of the rush hours as a high-speed highway with a speed limit of 80km/h or less. Especially traffic congestion within the ramp junction areas is becoming worse by the increased traffic and lack of links with the arterials around the urban freeway. So, the purpose in this study is to identify the traffic characteristics within the ramp junction areas of urban freeway, predict the average speed within the ramp junction areas based on the traffic characteristics identified, and finally prove the validity of the average speed predicted.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.467-476
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• 2010

Travel delay (TD) denotes a time difference between the running time of vehicle with a normal speed and the travel time of vehicle with a reduced speed for traversing the same segment of roadway, and is sometimes used as a measure of time delayed in the junction or bottleneck areas of roadway. Urban freeways in the foreign countries are often suffering from traffic delay within the entrance and exit ramp junction influence areas, as a freeway with the speed limit of 80 km/h or higher only during the rush hours, but those in our country are especially experiencing severe traffic delay on the mainline segments as well as within the entrance and exit ramp junction influence areas, as a freeway with the speed limit of 80 km/h or less regardless of the rush hours. So, the purpose in this study is to develop the models that could predict the travel delay within the ramp junction influence areas of urban freeway having the geographical features which differ from the expressway, and also examine the validity of the travel delay predictive models developed.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.175-185
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• 2000

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the rap junctions of freeway with 70mph speed limit. From the traffic analyses, and model construction and verification for delay prediction on the ramp junctions of freeway, the following results were obtained : ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junctions of freeway. ⅲ) The delay-occupancy curve showed a remarkable shift based on the occupancies observed : O$\_$d/〈9% and O$\_$d/$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under O$\_$d/$\geq$9%, but lowly for delay prediction on the ramp junctions of freeway under O$\_$d/〈9%. Rather, the driver characteristics or transportation conditions around the freeway were thought to be a little higher explanatory for the delay prediction under O$\_$d/〈9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.287-293
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• 2008

Density is used as the measure of effectiveness within the ramp junction influence area suggested in the KHCM 2005 in the LOS analysis of the ramp junction, and also density predictive models suggested in the KHCM 2005 is constructed based on the expressway with the speed limit of 100km/h or 110km/h in Korea. So, the density predictive models suggested in the KHCM 2005 are needed to verify if the models could be applied to the urban freeway with the speed limit of 80km/h or less, because the speed limits on most of the urban freeways in Korea are 80km/h or less. The purpose in this study is to construct and verify the appropriate density predictive model within the on-ramp merge influence area of the urban freeway by comparing with the USHCM 2000 and KHCM 2005 models.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.95-100
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• 2002

The first version of KHCM was Published in 1992 and is currently used in engineering Practice extensively. The study of new manual was initiated by Korea Institute of Construction Technology 1998 and is intended to be ready for publication by the year 2002. According to the field survey, the action of the individual merging vehicle creates turbulence in the vicinity of the ramp-freeway junction area. The purpose of this paper is to develop the model for Predicting the for entering the lanes 1 and 2($V_{12}$) and the density function at the influence zone by comがring the research works on the ramp junction in the USHCM 2000. The methodology has two major steps : the determination of the flow entering Lanes 1 and 2 immediately upstream of the merge influence area: and the density of the flow within the ramp influence area As a result of this paper the specific functions for such models are suggested through the regression analysis of data collected at four freeway fields in Korea.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.111-121
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• 1999

From the traffic analyses, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results obtained: ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy.ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period shown 10mph decrease when compared with the 24hours' average speed, but the speed did not show a big difference in the afternoon peak period.ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge sectionⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.59-66
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• 2006

This study was to construct the linear density predictive models on the on-ramp junctions in urban freeway. From the analyses of the real-time traffic characteristic data, and the construction and verification of the linear density predictive models, the models showed a considerable explanatory power with the determination coefficients ($R^2$) of over 0.7 between the density and speed data. Also, they showed a considerably high correlativeness with the correlation coefficients (r) of over 0.8 between the calculated density data and the expected ones estimated by the models.